SubsidieMeestersHow EXPectation and ATtention shape visual information processing in the human brain
EXPAT aims to uncover how expectation and attention influence visual information encoding in the human brain using advanced neuroimaging and analytical techniques.
Projectdetails
Introduction
Our behaviours and conscious experiences are profoundly shaped by what we see. Therefore, it is not surprising that unravelling the neural mechanisms of vision ranks among the top priorities of neuroscience. This poses the challenge of unravelling how our brain creates seamless and comprehensible visual experiences from the dizzying onslaught of visual information bombarding our retinae.
Role of Expectation and Attention
Previous research suggests that expectation and attention play a central role in coordinating this information extraction process. However, at present, deep insights into how these two top-down processes shape information processing in the human visual system remain elusive.
Objectives of EXPAT
EXPAT will address this outstanding knowledge gap by revealing how expectation and attention change natural image information encoding in the human brain across visual features, across brain areas, and across time. To this end, EXPAT sets itself the following three objectives:
- Revealing how expectation and attention change the specificity and efficiency of information encoding in the human visual cortex.
- Measuring the impact of expectation and attention on image information encoding across cortical brain areas and between-area information transfer.
- Obtaining insights into how expectation and attention change the chronology of visual information processing.
Investigating Feedback Mechanisms
Moreover, EXPAT will address the open question of whether or not attention and expectation effects in the visual cortex are mediated by the same or by different feedback mechanisms.
Methodology
These objectives will be realised by using several advanced methods, including:
- Various multivariate analyses of fMRI and EEG data.
- A deep convolutional network-based approach for creating ‘feature-reduced’ natural images.
- A multivariate brain connectivity measure.
- A psychophysical technique for measuring the informativeness of image features.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 1.999.815 |
| Totale projectbegroting | € 1.999.815 |
Tijdlijn
| Startdatum | 1-2-2023 |
| Einddatum | 31-1-2028 |
| Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- UNIVERSITAETSKLINIKUM HAMBURG-EPPENDORFpenvoerder
Land(en)
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It's about time: Towards a dynamic account of natural vision.
TIME aims to revolutionize vision research by integrating semantic understanding and active information sampling through advanced brain imaging and bio-inspired deep learning, enhancing insights into visual cognition.
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COREDIM aims to identify the core dimensions of visual object representations using neuroimaging, behavioral data, and AI, enhancing our understanding of visual processing in the brain.
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